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Tax attractiveness and the location of German-controlled subsidiaries

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This paper analyzes whether taxation has an influence on the location decisions of multinational enterprises. We employ a novel set of 22 tax variables, such as the taxation of dividends and capital gains, withholding taxes, the existence of a group taxation regime, and thin capitalization rules. Furthermore, we use the Tax Attractiveness Index, a new aggregate measure containing the 22 tax variables. Our count data regression analysis is based on a novel hand-collected dataset consisting of the subsidiaries of German DAX30 companies in 97 countries. Controlling for non-tax effects, we find that a country’s tax environment has a significantly positive effect on the number of German-controlled subsidiaries and, therefore, on the location decisions of German multinational enterprises. Specifically, our analysis reveals that German multinational firms place affiliates in countries that offer favorable statutory tax rates, withholding taxes, double tax treaty networks, and holding incentives. Additionally, we find that the Tax Attractiveness Index has explanatory power in subsidiary location decisions and, therefore, it can be used as alternative composite measure, for example, when 22 single tax variables are not at disposal.

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  1. The stock of German companies’ investment abroad has increased by more than 40 % over the 5 years from 2004 to 2009 and has grown from approximately 30 to 40 % of the size of the German GDP (Deutsche Bundesbank 2007, 2013).

  2. Economic theory distinguishes between two main driving forces for becoming a multinational firm. According to the vertical model, differences in factor prices across countries lead to the emergence of multinational companies (Helpman 1984, 1985). According to the horizontal model, the internationalization decision is motivated by market access (Markusen 1984, 2002).

  3. Simmons (2003) constructed a composite index for seven countries for the year 1999.

  4. In other contexts, the application of indices is widely accepted. A famous example is the creditor rights index introduced by La Porta et al. (1998) that has been applied in many subsequent articles (Djankov et al. 2007; Spamann 2010). In the sense of Hung (2000), Jacob and Goncharov (2014) construct a tax accrual index that counts accrual norms codified in tax law.

  5. We include all legally independent entities held by a parent company. We use the terms “subsidiary” and “affiliate” interchangeably.

  6. DAX30 is the major German stock market index (Deutscher Aktien Index) and comprises the 30 largest listed companies based on order book volume and market capitalization.

  7. According to Section 8b of the German corporate income tax code (Körperschaftsteuergesetz), dividends distributed by national or foreign affiliates can be received free of tax. Only 5 % of dividends are taxed as non-deductible operating expenditures.

  8. We use model-based effective tax rates based on the methodology of Devereux and Griffith (2003), which are widely used in tax research, as an alternative measure of tax attractiveness, and calculated by Endres et al. (2014) for 35 countries and the years 1998–2014.

  9. Hines (1997) and Devereux (2007) provide comprehensive reviews of the existing literature. Based on previous studies, De Mooij and Ederveen (2003, 2006) and Feld and Heckemeyer (2011) conduct meta-analyses. Early contributions in the field of taxation and FDI are based on aggregate FDI flows (see Hartman 1984 for pioneering work). Other analyses use aggregated firm-level data on property, plant, and equipment to investigate real economic activity more accurately than FDI in its broad definition (Hines and Rice 1994; Grubert and Mutti 1991, 2000; Altshuler et al. 2001). However, due to the underlying data structure, they are not capable of disentangling the discrete location choice and the subsequent continuous choice of the investment level. With the availability of firm-level data, the number of studies examining international location decisions has increased (see the framework developed by Devereux (2007).

  10. There are two kinds of effective tax rates. The effective marginal tax rate refers to the influence of taxation on an investment that only earns the cost of capital, while the effective average tax rate represents the impact of taxes, assuming a higher profitability of the underlying investment project. A different type of effective tax rate is analyzed by Markle and Shackelford (2012). They empirically investigate accounting effective tax rates based on financial statement information. These accounting effective tax rates are often in the focus of investors, but optimization of accounting effective tax rates can lead to sub-optimal investment decisions (Müller and Sureth 2010).

  11. Papke (1991) is the only exception and uses simulation-based effective tax rates.

  12. The aforementioned Gumpert et al. (2012) is a recent exception.

  13. Due to multicollinearity reasons, we only include 20 tax variables in our disaggregated regression analyses.

  14. The set of tax variables composing the Tax Attractiveness Index described in Keller and Schanz (2013) has been slightly adjusted to reflect the research question and the perspective of German multinational companies in this study. We include depreciation rules, R&D incentives, amount limitations for loss carry forward and loss carry back rules, withholding taxes on dividends, interest and royalties paid to a German parent, and exclude the EU dummy.

  15. Since we use the maximum value observed among all countries within a year to scale our variables in some instances, we cannot infer absolute improvements of these countries’ tax systems over time. If, for example, a country’s value increases, it has improved its position relative to the most attractive country, but that does not necessarily mean that it has made its tax code more attractive. It could well be that the formerly most attractive country became less attractive. Given that we observe only limited within-country variance of countries’ tax rules over time in our sample and since it can well be argued that companies take a relative rather than an absolute perspective when making their location decision, we argue that this is only a minor problem.

  16. We use the TAX as our primary measure since is that it is the more universal measure. While the TAX_sig is tailored to specific subsidiary location decisions, the TAX contains more tax variables and therefore (potentially) is relevant for other types of corporate location decisions (e.g. location of assets such as patents).

  17. In its original version, the Tax Attractiveness Index contains a dummy variable indicating whether the respective country is part of the European Union and, therefore, benefits from the EU directives (Keller and Schanz 2013). However, in this study, we replace the dummy variable with the specific withholding tax rates to Germany, making our analysis more precise for our Germany-related research question.

  18. There are existing measures of R&D incentives (Warda 2001; Lohse et al. 2012). However, these measures also abstract from many of the above mentioned details and are available only for a limited time horizon and set of countries.

  19. Instead of 7.1 %, as assumed by Endres et al. (2014), we assume a nominal interest rate of 3.76 %, the average yield of 10-year German government bonds over the sample horizon (2005–2009). We chose commercial property as a representative asset class, since it is relevant for a broad variety of companies from different industries, and its depreciation rules are best documented for a large number of countries (source: Ernst & Young Worldwide Corporate Tax Guide). A cross-check with depreciation rates on machinery for countries with available data reveals a correlation of approx. +0.5.

  20. With 0.689, countries identified as tax havens by Hines and Rice (1994) having a significantly higher average index value than non-haven countries (0.480). 12 out of the most attractive 20 countries are identified as tax havens. However, there are several tax havens, such as Lebanon and Panama, which do not appear among the highest ranking peers according to the Tax Attractiveness Index. A similar result is found, if the tax haven definition by the OECD is used (OECD 2000, 2009).

  21. See Section 26 of the Foreign Trade and Payments Act (Außenwirtschaftsgesetz) in connection with the Foreign Trade and Payments Regulation (Außenwirtschaftsverordnung).

  22. For further information about MiDi, see Lipponer (2009).

  23. Furthermore, we do not include Fresenius Medical Care AG & Co. KGaA (FMC), since it is owned and consolidated by Fresenius SE. An inclusion of both members of the DAX30 would lead to double-counting the subsidiaries of FMC.

  24. We are able to differentiate between consolidated affiliates, non-consolidated affiliates, associated companies, and joint ventures. However, about 70 % of the subsidiaries included in our initial sample are consolidated affiliates.

  25. The following example illustrates our approach: if parent company 1 operates five affiliates in Spain in year 2006, then Number Subsidiaries equals five. The five Spanish subsidiaries count as one observation.

  26. We add € 1 to the sum before calculating the natural logarithm in order not to eliminate observations with € 0 equity.

  27. The R2 for the disaggregate non-logarithmic regression of 0.07 compares to 0.47 for the logarithmic regression.

  28. If we exclude Rule of Law and Voice & Accountability, the two control variables for which we do not have data for the British Virgin Islands and Jersey, and rerun our main regressions including the two countries, the results do not change materially (not reported).

  29. Thus, we finally capture 51,075 of the initial 74,396 subsidiaries.

  30. The likelihood-ratio test of the overdispersion parameter (alpha) in the zero-inflated negative binomial model reveals that it is significantly different from zero and therefore, that data are overdispersed. Furthermore, the Chi square test of a Poisson model rejects the hypothesis that it fits well at the one percent level.

  31. Likelihood-ratio tests of the overdispersion parameters (alpha) reveal that it is significantly different from zero at the one percent level. Therefore, the negative binomial model is preferred over the Poisson model.

  32. Becker et al. (2012) and Overesch and Wamser (2009) also opt for this version of the negative binomial model.

  33. The Vuong test statistic (z = 21.13) based on our main model specification is significant at the one percent level.

  34. The within-country variance of the Tax Attractiveness Index (0.025) is substantially lower than the between-country variance (0.145). We would expect to see more variables to show significant effects if a longer time horizon is observed over which the tax variables exhibit more variation.

  35. The clustering by country-year results in lower standard errors. To apply the most conservative specification, we therefore cluster standard errors by country. Moreover, standard errors allow for heteroskedasticity.

  36. The corresponding formula can be written as: 1-(abs[GDP per capita it  − GDP per capita DEU t ]/max[GDP per capita it , GDP per capita DEU t ]) (Buch et al. 2005). GDP per capita is measured in constant U.S. dollars based on the year 2000, respectively.

  37. This is in line with the gravity approach that explains international activity by a combination of mass variables (e.g., GDP and population) and distance variables (Bellak et al. 2009).

  38. Since the parameters are highly correlated with each other, we are not able to include all six indicators.

  39. Note that the Tax Attractiveness Index value for Germany excludes the withholding tax rates on dividends, interest, and royalties paid to a German parent. Therefore, comparisons of this value with other countries are only approximations.

  40. A 10 % point higher statutory tax rate translates into a 0.250 index point lower value of the corresponding scaled tax variable (2009), which is used in our regressions.

  41. To prevent the extensive use of debt financing, some countries enforce thin capitalization rules.

  42. Mintz (2004) suggests that financial structures involving an intermediate entity in a low-tax country are used to achieve a double dip of interest deductions. In such cases, the parent company borrows capital and passes it on to the intermediate company in the form of equity. The intermediate company, in turn, lends the capital to another subsidiary located in a high-tax country. Hence, interest can be deducted twice, once at the level of the high-tax affiliate and again at the level of the parent company. Interest is taxed at the level of the intermediate group unit. The overall group tax burden can be decreased if the local tax rate of the interposed company is comparably low or if interest income is subject to a reduced tax rate.

  43. A notional interest deduction applies, for instance, in Belgium. It allows the deduction of a fictitious interest on equity.

  44. Before calculating the natural logarithm, we add € 1 to the sum in order not to drop observations with € 0 equity.

  45. Zero is not a frequent observation for Number Subsidiaries (all). Therefore, we refrain from using a zero-inflated negative binomial model.

  46. When running regressions for each year separately, our results for the aggregate regression hold. When including the individual tax variables separately, our model does not converge for the year 2007. When looking at the remaining years, we find significant evidence for the four tax variables that show significant coefficients in the main regression (Table 3) in single years. In addition, we find significantly positive coefficients for withholding tax rates on dividends (no treaty), group relief provisions, as well as (unexpected) significantly negative coefficients for thin capitalization rules, the personal income tax rate and loss carry forward amount limitations in single years (results not reported).

  47. The correlation between TAX_sig_EW and TAX_sig is 0.99. Regression results for TAX_sig_EW are almost identical to those for TAX_sig.

  48. As indicated in the previous section, we use all components of the Tax Attractiveness Index except for withholding taxes on royalties paid to a German parent and loss carry back amount limitations due to multicollinearity concerns. Rule of Law, the other factor excluded from the regression, is not part of the index.

  49. Permanyer (2011) also finds two indices, the Gender Empowerment Measure (GEM) and the Gender Relative Status (GRS), which are not fully robust against the choice of alternating weighting schemes.

  50. We use the mean effective average tax rates at the corporate level shown in section C of Endres et al. (2014).

  51. Overesch and Wamser (2009, 2010) calculate effective tax rates based on a methodology similar to Endres et al. (2014); therefore, we can compare our results to theirs.

  52. Furthermore, Overesch and Wamser (2010) can distinguish between industries and types of FDI which is not possible with our data at hand.

  53. The AIC assumes a value of 19,611 for specification (1) and 19,647 for specification (2).


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We thank Martin Jacob, Igor Goncharov, Martin Ruf, Michael Overesch, Maximilian André Müller, Caspar David Peter, Holger Theßeling, Robert Risse, Wolfgang Schön, Kai Konrad, Pia Kortebusch, Caren Sureth, Sebastian Schanz and delegates from the European Accounting Association conference in Paris 2013, the German Academic Association for Business Research conference in Würzburg 2013, the Quantitative Research in Taxation conference ( in Bochum 2013, workshop participants at WHU—Otto Beisheim School of Management, Otto-von-Guericke University Magdeburg, Ludwig-Maximilians-University Munich, and the Max Planck Institute for Tax Law and Public Finance, Munich, as well as two anonymous referees for their helpful comments and suggestions.

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Correspondence to Deborah Schanz.


Appendix 1: Variable definitions

Tax Attractiveness Index

Index covering 22 different tax factors. For Germany, TAX consists of 19 components excluding withholding tax rates to Germany on dividends, interest, and royalties. The index represents host country i’s tax attractiveness and is constrained to values between zero and one. The more the index approaches one, the more attractive the tax environment that host country i offers. The index is measured on an annual basis (2005–2009). Data sources: the Global Corporate Tax Handbook and the European Tax Handbook published by the International Bureau of Fiscal Documentation (IBFD), PricewaterhouseCoopers’ Corporate Taxes—Worldwide Summaries and Individual Taxes—Worldwide Summaries, Ernst & Young’s Worldwide Corporate Tax Guide, Deloitte’s Taxation and Investment Guides, KPMG’s Corporate Tax Rate Survey and Individual Income Tax Rate Survey, and the OECD tax database


Logarithm of host country i’s gross domestic product measured in constant U.S. dollars based on the year 2000. GDP is measured on an annual basis. Data sources: World Development Indicators of the World Bank. For Taiwan, we source data from the National Statistics of China (Taiwan) ( and the Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. Taiwan ( For the Netherlands Antilles, we source data from the Central Bureau of Statistics Curaçao ( and Statistics Netherlands ( For the Cayman Islands, we source data from the Economics and Statistics Office, Government of the Cayman Islands ( For Guernsey, we source data from the States of Guernsey (


An index reflecting the difference between Germany’s gross domestic product per capita and the gross domestic product per capita of host country i. The index is defined as one minus the ratio of the absolute value of host country i’s gross domestic product per capita minus Germany’s gross domestic product per capita to the higher of both gross domestic products per capita. Gross domestic product per capita is measured in constant U.S. dollars based on the year 2000, respectively. The index uses values between one and zero; a higher score indicates that countries are more similar. Similarity is measured on an annual basis. Data source: World Development Indicators of the World Bank. For Taiwan, we source data from the National Statistics of China (Taiwan) ( and the Directorate-General of Budget, Accounting and Statistics, Executive Yuan, R.O.C. Taiwan ( For the Netherlands Antilles, we source data from the Central Bureau of Statistics Curaçao ( and Statistics Netherlands ( For the Cayman Islands, we source data from the Economics and Statistics Office, Government of the Cayman Islands ( For Guernsey, we source data from the States of Guernsey (


The great circle distance between Germany’s main agglomeration and host country i’s main agglomeration, weighted by the share of the agglomeration in the overall country’s population, respectively. Data source: Centre d’Etudes Prospectives et d’Informations Internationales (CEPII). For Liechtenstein, we take the Swiss value (Zurich). For Montenegro, we take the Serbian value (Belgrade). For Guernsey, we take the value of Great Britain (London)


A dummy variable obtaining the value of one if host country i shares a border with Germany

Rule of Law

Reflecting the level to which negotiators have confidence in and adhere to the rules of society. It captures particularly the qualities of contract enforcement, property rights, the police, as well as the probability of crime and violence in host country i. Rule of Law may range between −2.5 and 2.5 and is measured on an annual basis. Data source: World Governance Indicators of the World Bank. For Guernsey, we take the value of Great Britain

Voice & Accountability

Indicating the degree to which citizens of host country i are given the possibility to elect their government. In addition, it represents the extent to which the freedom of expression, the freedom of association, and a free media are established in host country i. Voice & Accountability may range between −2.5 and 2.5, and is measured on an annual basis. Data source: World Governance Indicators of the World Bank. For Guernsey, we take the value of Great Britain

Appendix 2: Additional analysis

See Tables 7, 8, 9, 10 and 11.

Table 7 Measurement of tax variables
Table 8 Tax attractiveness index per country
Table 9 Sample Selection
Table 10 Correlation between different dependent variables and country-level controls
Table 11 Robustness test—change in number of subsidiaries

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Schanz, D., Dinkel, A. & Keller, S. Tax attractiveness and the location of German-controlled subsidiaries. Rev Manag Sci 11, 251–297 (2017).

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